Urinary Luteinizing Hormone Tests: Which Concentration Threshold Best Predicts Ovulation?
Bibliographic record
Abstract
OBJECTIVE: To study the best possible luteinizing hormone (LH) threshold to predict ovulation within the 24, 48, and 72 h. DESIGN: Observational study. SETTING: Multicenter collaborative study. PATIENTS: A total of 107 women. INTERVENTIONS: Women collected daily first morning urine for hormonal assessment and underwent serial ovarian ultrasound. This is a secondary analysis of 283 cycles. MAIN OUTCOME MEASURES: The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios were estimated for varying ranges of LH thresholds. Receiver operating characteristic curves and cost-benefit ratios were used to estimate the best thresholds to predict ovulation. RESULTS: The best scenario to predict ovulation at random was within 24 h after the first single positive test. The false-positive rate was found to increase as (1) the cycle progressed or (2) two or three consecutive tests were used, or (3) ovulation was predicted within 48 or 72 h. Testing earlier in the cycle increases the predictive value of the test. The ideal thresholds to predict ovulation ranged between 25 and 30 mIU/ml with a PPV (50-60%), NPV (98%), LR+ (20-30), and LR- (0.5). At least, one day with LH ≥25 mIU/ml followed by three negatives (LH <25) occurred before ovulation in 31% of all cycles. When used throughout the cycle and evaluated together, peak-fertility type mucus with a positive LH test ≥25 mIU/ml provides a higher specificity than either mucus or LH testing alone (97-99 vs. 77-95 vs. 91%, respectively). CONCLUSION: We identified that beginning LH testing earlier in the cycle (day 7) with a threshold of 25-30 mIU/ml may present the best predictive value for ovulation within 24 h. However, prediction by LH testing alone may be affected negatively by several confounding factors so LH testing alone should not be used to define the end of the fertile window. Complementary markers should be further investigated to predict ovulation and identify the fertile window. The use of the peak cervical mucus along with an LH test may provide a higher specificity and predictive value than either of them alone. We recommend that manufacturers disclose their tests' threshold to the public.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".